A high-sensitivity high-throughput LCMS platform for single-cell proteomics and low sample amount analysis

Importance of the topic

Single-cell proteomics and analysis of minute sample quantities demand workflows that deliver exceptional sensitivity without sacrificing throughput. Achieving reproducible data quality under ultra-low flow conditions is critical for applications in biological and clinical research.

Objectives and study overview

This study aimed to develop a high-sensitivity, high-throughput nano-LC-MS platform compatible with single-cell proteomics (SCP) and limited sample amount (LSA) analysis. The approach was benchmarked for both data-dependent (DDA) and data-independent acquisition (DIA) strategies across varying gradient lengths and sample loads.

Methodology and instrumentation

• LC system: Thermo Fisher™ Vanquish™ Neo UHPLC with direct injection at 1500 bar and 0.25 ng HeLa digest loads.
• Column: 50 µm I.D. × 15 cm PepMap C18, 2 µm particle size.
• Flow rate: 100 nL/min with gradients from 10 to 50 min.
• Emitter: 10 µm I.D. nano-ESI for optimized ionization.
• MS: Thermo Scientific™ Orbitrap Exploris™ 480 with FAIMS Pro interface.
• Acquisition: DDA using SEQUEST™ HT and INFERYS™ rescoring in Proteome Discoverer, plus CHIMERYS™ spectrum deconvolution; DIA with Spectronaut 16 and DIA-NN 1.8.
• Samples: 250 pg–5 ng HeLa tryptic digest; HeLa Digest/PRTC standard preparation in 0.1% formic acid.
• Data analysis: R scripts, FDR <1% at peptide and protein levels.

Main results and discussion

• Five optimized methods enabling 24–72 samples/day with 55–85% MS utilization.
• In DDA, a 10-min gradient from 250 pg HeLa yielded ~800 protein groups; AI-driven CHIMERYS deconvolution increased IDs to ~1,800.
• DIA analysis achieved >2,000 protein groups from 250 pg in a 10-min gradient, outperforming library-free approaches.
• Low variation in retention times and protein quantification confirmed high reproducibility.
• Ion accumulation time proved more critical than scan speed for maximizing peptide and protein identifications in low sample scenarios.

Benefits and practical applications

This platform offers a balanced solution for high-throughput, high-sensitivity proteomics, allowing large-cohort single-cell and limited-sample studies. It integrates seamlessly with LFQ and TMT workflows and advances industry benchmarks for proteome coverage in DDA and DIA modes.

Future trends and possible applications

• Application to real-world single-cell and LSA biological studies.
• Further integration of AI-driven spectrum deconvolution and advanced acquisition algorithms.
• Development of multiplexed assays and increased sample multiplexing capacity.
• Improvements in column technology and fluidic designs to enhance robustness.

Conclusion

The developed nano-LC-MS platform establishes new standards for sensitivity and throughput in single-cell and limited-sample proteomics. By combining ultra-low flow separations, advanced MS acquisition, and AI-driven data processing, it unlocks deep proteome profiling from sub-nanogram samples.

References

1. R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
2. Stejskal K, Op de Beeck J, et al. Ultrasensitive NanoLC-MS of Subnanogram Protein Samples Using Second Generation Micropillar Array LC Technology with Orbitrap Exploris 480 MS and FAIMS Pro interface. Anal. Chem. 2021, 93(25):8704–8710.